SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance.

Jason Stahlecker,Mehmet Direnç Mungan,Erik Mingyar,Nadine Ziemert

doi:10.3390/molecules26010144

Abstract

The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.

Highlights

Lena KellerWith the increasing number of drug-resistant bacteria, antimicrobial resistance has become a global health threat [1]
The main approach of these tools is the identification of locally clustered groups of genes called biosynthetic gene clusters (BGCs), which are in conjunction responsible for the synthesis of secondary metabolites [9]
For the proof of concept of our proposed method, first we examined bacterial strains reported for antibiotic production with known resistance mechanisms shown in Table 1, to test if there is a significant difference between neighborhoods of gene of interest (NGIs) structures of regular housekeeping genes and genes responsible for self-resistance

Summary

Introduction

Lena KellerWith the increasing number of drug-resistant bacteria, antimicrobial resistance has become a global health threat [1]. As the number of approved drugs have been decreasing over the past few decades, finding new compounds to feed the antibiotic discovery pipeline has become a crucial task [2]. Most of the antibiotics are derived from secondary metabolites (SMs) produced by fungal and bacterial organisms [3]. Many of these so-called natural products were found by labor-intensive methods such as screening biological samples for desired bioactivities. These traditional methods have been losing their efficiency, due to their high rediscovery rates [4]. The main approach of these tools is the identification of locally clustered groups of genes called biosynthetic gene clusters (BGCs), which are in conjunction responsible for the synthesis of secondary metabolites [9]

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Conclusion